A Practical Multi-Stage Docker Build for Python APIs

<p>When I joined Ericsson's R&amp;D team as an intern, our development environment had a problem that every engineer on the team silently accepted as normal: spinning up a full

<p>We've all been there: you whip up a simple microservice in Python, write a quick Dockerfile, run <code>docker build</code>, and suddenly your container image weighs almost

<h2> Security Is Part of Reliability </h2> <p>SREs think about availability, latency, and throughput. But a security breach is just another type of incident — often the worst

<h2> The Problem with Fat Images </h2> <p>We've all been there: you pull a Docker image, and it's 1.2GB. You run a simple Node app, and the image is bigger than your entire OS.

<h2> Prologue: The Initial Skepticism </h2> <p>I am a software developer with over 8 years of experience building products. Over the last few years, the name "Docker" has been

<p>"Works on my machine" is one of the oldest jokes in software, and it stopped being funny the first time it cost me a weekend. The code was fine. The environment wasn't. A

<p>When I started working with Docker, I made the same <br /> mistake most beginners make — I used the full base image <br /> and copied everything into the container without

<h2> <strong>Docker Competencies: Part 1/3 (BASIC)</strong> </h2> <p><em>From "I've heard of it" to "I can ship it"</em></p> <p><strong>Task 1: Create a Multi-Stage